The stock market plays a vital role in the economic and social organization of many
countries. Since stock price time series are highly noisy, nonparametric, volatility …

Although different studies are caried out by deep learning models for financial markets
sentiment analysis, there is a lack of specific embedding method that regards the domain …

Forecasting stock price movements is an important task for investors and traders, though still
very difficult due to the unstable nature and complex behavior of the stock market …

Sentiment analysis technologies have a strong impact on financial markets. In recent years
there has been increasing interest in analyzing the sentiment of investors. The objective of …

This paper examines the impact of integrating sentiment data from Twitter with historical
stock prices to enhance stock market prediction accuracy. The study employs a comparative …

Financial text‐based risk prediction is an important subset for financial analysis. Through
automatic analysis of public financial comments, fundamentals on current financial …

With a speedy development in Natural Language processing, the financial sector meets the
demand of analyzing a large quantity of financial text data. Several recent research has …

To make the financial decision from the Sentiment Analysis of Financial Tweets. To predict
the sentiment of financial tweets using a novel Decision Tree with improved accuracy over K …

This study investigates the impact of social media sentiment on indirect real estate market
returns by utilizing a comprehensive natural language processing approach to identify …

In recent years, many cases of deep neural networks failing dramatically when faced with
adversarial or real-world examples have been reported. Such failures, which are quite hard …